Skip to content
icon icon Building AI Intuition

Connecting the dots...

icon icon Building AI Intuition

Connecting the dots...

  • Home
  • ML Basics
  • Model Intuition
  • Encryption
  • Privacy Tech
  • Musings
  • About
  • Home
  • ML Basics
  • Model Intuition
  • Encryption
  • Privacy Tech
  • Musings
  • About
Close

Search

Subscribe
icon icon Building AI Intuition

Connecting the dots...

icon icon Building AI Intuition

Connecting the dots...

  • Home
  • ML Basics
  • Model Intuition
  • Encryption
  • Privacy Tech
  • Musings
  • About
  • Home
  • ML Basics
  • Model Intuition
  • Encryption
  • Privacy Tech
  • Musings
  • About
Close

Search

Subscribe
Recent Posts
March 1, 2026
Teaching AI Models: Gradient Descent
March 1, 2026
Needle in the Haystack: Embedding Training and Context Rot
March 1, 2026
Measuring Meaning: Cosine Similarity
February 28, 2026
AI Paradigm Shift: From Rules to Patterns
February 16, 2026
Seq2Seq Models: Basics behind LLMs
February 16, 2026
Word2Vec: Start of Dense Embeddings
February 13, 2026
Advertising in the Age of AI
February 8, 2026
Breaking the “Unbreakable” Encryption – Part 2
February 8, 2026
Breaking the “Unbreakable” Encryption – Part 1
February 8, 2026
ML Foundations – Linear Combinations to Logistic Regression
February 2, 2026
Privacy Enhancing Technologies – Introduction
February 2, 2026
Privacy Enhancing Technologies (PETs) — Part 3
February 2, 2026
Privacy Enhancing Technologies (PETs) — Part 2
February 2, 2026
Privacy Enhancing Technologies (PETs) — Part 1
February 2, 2026
An Intuitive Guide to CNNs and RNNs
February 2, 2026
Making Sense Of Embeddings
November 9, 2025
How CNNs Actually Work
August 17, 2025
How Smart Vector Search Works
Machine Learning Basics

Making Sense Of Embeddings

Post 2/N When you search on Amazon for “running shoes,” the system doesn’t just look for those exact…

Machine Learning Basics

How Smart Vector Search Works

In the ever-evolving world, the art of forging genuine connections remains timeless. Whether it’s with colleagues,…

Machine Learning Basics

ML Foundations – Linear Combinations to Logistic Regression

Post 1a/N Every machine learning model — from simple house price predictors to neural networks with billions of…

Privacy Tech

Privacy Enhancing Technologies (PETs) — Part 1

How Your Data Gets Protected Every time you browse a website, click an ad, or make a purchase, data flows through…

Encryption

Breaking the “Unbreakable” Encryption – Part 2

In Part 1, we covered the “Safe” (Symmetric) and the “Mailbox” (Asymmetric). The TL;DR: we use…

Musings

Advertising in the Age of AI

When you search for a product today, ads quietly shape what you notice. When you scroll Instagram, ads compete for…

Browse Tag

cnn

1 Article

An Intuitive Guide to CNNs and RNNs

Archit Sharma By Archit Sharma
6 Min Read

When your phone recognizes “Hey Siri,” a CNN is probably listening. When Google Translate converts your sentence into French, an RNN (or its descendants) is doing the heavy lifting. Both are neural networks, but they’re built for fundamentally different…

Read More
Model Intuition

Categories

icons8 pencil 100
ML Basics

Back to the basics

screenshot 1
Model Intuition

Build model intuition

icons8 lock 100 (1)
Encryption

How encryption works

icons8 gears 100
Privacy Tech

What protects privacy

screenshot 4
Musings

Writing is thinking

Recent Posts

  • Teaching AI Models: Gradient Descent
  • Needle in the Haystack: Embedding Training and Context Rot
  • Measuring Meaning: Cosine Similarity
  • AI Paradigm Shift: From Rules to Patterns
  • Seq2Seq Models: Basics behind LLMs
  • Word2Vec: Start of Dense Embeddings
  • Advertising in the Age of AI
  • Breaking the “Unbreakable” Encryption – Part 2
  • Breaking the “Unbreakable” Encryption – Part 1
  • ML Foundations – Linear Combinations to Logistic Regression
Copyright 2026 — Building AI Intuition. All rights reserved. Blogsy WordPress Theme